Jonghyun Bae

Bio: Jonghyun Bae is an academic researcher from Yonsei University. The author has contributed to research in topics: Interpolation & Stairstep interpolation. The author has an hindex of 5, co-authored 9 publications receiving 91 citations.

Natural hdr image tone mapping based on retinex

Abstract: In this paper, new k factor decision method and highlight compression operator are proposed to enhance the appearance and naturalness of rendered High Dynamic Range (HDR) images. The retinex algorithm is one of the outstanding local operators, which well preserves local contrast in highlights. However, the retinex algorithm gives a worse overall appearance and undistinguishable dark area contrast than global operators or other local operators in some cases. The most prominent improvement of the proposed method is that the decision method of the k factor, which is one of the parameters in retinex algorithm, is proposed by using the dynamic range in images. The proposed parameter decision method enhances the overall quality and preference of the image and solves any parameter setting problems. Also, dark area details become more distinguishable by the highlight compression operator. According to the results of many HDR image experiments, the proposed method shows better rendering in terms of naturalness and dark area details than the previous tone-mapping algorithm.1.

Multidirectional edge-directed interpolation with region division for natural images

Abstract: Yujin Yun, Jonghyun Bae, and Jaeseok KimYonsei University, Department of Electrical and ElectronicEngineering, 50 Yonsei-ro, Seodaemun-gu, Seoul,Republic of KoreaE-mail: yujin.yun@yonsei.ac.krAbstract. A multidirectional edge-directed interpolation algo-rithm that features a region division method is proposed. Inthe proposed method, an interpolation pixel is newly modeledas a weighted sum of 12 neighboring pixels representing 12different directions. Each weight is estimated by Wiener filtertheory using geometric duality. The proposed method fordividing the interpolation region reduces the heavy computa-tional complexity of the proposed model. Analyzing edgecontinuities, the model divides an image into three regions,and only strong edge regions are interpolated. Simulationresults show that several directional edges are restoredclearly in a subjective test, with fair performance in an objec-tive test.

Adaptive multidirectional edge directed interpolation for selected edge regions

Abstract: This paper proposes an adaptive edge-directed interpolation algorithm using multidirectional neighbor pixels. In order to restore multidirectional edges, a missing pixel is estimated as a weighted sum of 12 neighbor pixels. Based on the geometric duality between a low resolution image and a high resolution image, interpolation coefficients are predicted using Wiener filter theory. In order to reduce the computational complexity, interpolation region selection method is also proposed. An edge map for a low resolution image is obtained by canny edge detector. By analyzing edge continuities, only long edge regions are interpolated using 12 neighbor pixels. Short edge regions are interpolated by new edge-directed interpolation, and even regions are interpolated by a linear interpolation. Simulation results show that a proposed method restores major edges with several directions better than other methods in subjective tests while showing fair performance in objective tests.

A new edge directed interpolation algorithm using accurate estimation of edge directional covariance

Abstract: This paper proposes an edge-directed interpolation algorithm to enhance the quality of natural images which are captured by low-resolution camera installed on car or CCTV. Based on the accurate estimation of edge directional covariance between low-resolution and high-resolution image, local covariance coefficients extracted from the low-resolution image has been adapted for the interpolation to obtain the high-resolution image. DCT (Discrete Cosine Transform) kernel function is used in order to reflect the multi-directional edge accurately without increasing of complexity. Simulation result shows that our new interpolation algorithm significantly improves the subjective quality of the interpolated images compared with conventional linear interpolation and NEDI one. It also demonstrates the improvements of objective metrics such as PSNR, SSIM(structural similarity index measurement) and WEA (Wiener filter coefficients Estimation Accuracy) which are used for the accuracy estimation of directionality.

Adaptive tone-mapping operator for HDR images based on image statistics

Abstract: In this paper, we present a novel segmentation method for displaying high dynamic range image based on K-means clustering. The new segmentation method uses statistical features of an image in a logarithmic luminance domain. Each divided region is applied to different global tone mapping operators respectively. The global tone mapping operator is a logarithmic tone mapping with a different user parameters. The parameters for applying to each region are calculated using a centroid which is obtained from K-means clustering. According to results of many HDR image experiments, we demonstrate that our method is faster than other local tone mapping operators and improves an image rendering performance in terms of dark area details and contrast enhancement.

Fast multi-exposure image fusion with median filter and recursive filter

Abstract: This paper proposes a weighted sum based multi-exposure image fusion method which consists of two main steps: three image features composed of local contrast, brightness and color dissimilarity are first measured to estimate the weight maps refined by recursive filtering. Then, the fused image is constructed by weighted sum of source images. The main advantage of the proposed method lies in a recursive filter based weight map refinement step which is able to obtain accurate weight maps for image fusion. Another advantage is that a novel histogram equalization and median filter based motion detection method is proposed for fusing multi-exposure images in dynamic scenes which contain motion objects. Furthermore, the proposed method is quite fast and thus can be directly used for most consumer cameras. Experimental results demonstrate the superiority of the proposed method in terms of subjective and objective evaluation.

A Tone-Mapping Technique Based on Histogram Using a Sensitivity Model of the Human Visual System

Abstract: High-dynamic-range (HDR) images require tone mapping to be displayed properly on lower dynamic range devices. In this paper, a tone-mapping algorithm that uses histogram of luminance to construct a lookup table (LUT) for tone mapping is presented. Characteristics of the human visual system (HVS) are used to give more importance to visually distinguishable intensities while constructing the histogram bins. The method begins with constructing a histogram of the luminance channel, using bins that are perceived to be uniformly spaced by the HVS. Next, a refinement step is used, which removes the pixels from the bins that are indistinguishable by the HVS. Finally, the available display levels are distributed among the bins proportionate to the pixels counts thus giving due consideration to the visual contribution of each bin in the image. Quality assessment using both quantitative evaluations and user studies suggests that the presented algorithm produces tone-mapped images that are visually pleasant and preserve details of the original image better than the existing methods. Finally, implementation details of the algorithm on GPU for parallel processing are presented, which could achieve a significant gain in speed over CPU-based implementation.

Multidirectional Weighted Interpolation and Refinement Method for Bayer Pattern CFA Demosaicking

Abstract: This paper presents a novel multidirectional weighted interpolation algorithm for color filter array interpolation. Our proposed method has two contributions to demosaicking. First, different from conventional interpolation methods based on two directions or four directions, the proposed method exploits to greater degree correlations among neighboring pixels along eight directions to improve the interpolation performance. Second, we propose an efficient postprocessing method to reduce interpolation artifacts based on the color difference planes. Compared with conventional state-of-the-art demosaicking algorithms, our experimental results show the proposed algorithm provides superior performance in both objective and subjective image quality. Furthermore, this implementation has moderate computational complexity.

Multidirectional Weighted Interpolation and Refinement Method for Bayer Pattern

Abstract: This paper presents a novel multidirectional weighted interpolation algorithm for color filter array inter- polation. Our proposed method has two contributions to demosaicking. First, different from conventional interpolation methods based on two directions or four directions, the proposed method exploits to greater degree correlations among neighboring pixels along eight directions to improve the interpolation perfor- mance. Second, we propose an efficient postprocessing method to reduce interpolation artifacts based on the color difference planes. Compared with conventional state-of-the-art demosaick- ing algorithms, our experimental results show the proposed algorithm provides superior performance in both objective and subjective image quality. Furthermore, this implementation has moderate computational complexity.

Bayer Pattern CFA Demosaicking Based on Multi-Directional Weighted Interpolation and Guided Filter

Abstract: In this letter, we proposed a new framework for color image demosaicking by using different strategies on green (G) and red/blue (R/B) components. Firstly, for G component, the missing samples are estimated by eight-direction weighted interpolation via exploiting spatial and spectral correlations of neighboring pixels. The G plane can be well reconstructed by considering the joint contribution of pre-estimations along eight interpolation directions with different weighting factors. Secondly, we estimate R/B components using guided filter with the reconstructed G plane as guidance image. Simulation results verify that, the proposed framework performs better than state-of-the-art demosaicking methods in term of color peak signal-to-noise ratio (CPSNR) and feature similarity index measure (FSIM), as well as higher visual quality.